Lower ionosphere is difficult to probe for conventional measurements, as its altitude range is too low for the satellite and too high for atmospheric balloons. Recently, an alternative method to study lower ionosphere is using lightning signatures. In this work，we investigate the daytime fluctuations of lower ionosphere by analyzing the time domain VLF/LF waveform emitted by Narrow Bipolar Events (NBEs), which were recorded by an eight-station lightning location network called Jianghuai-Area Sferic Array (JASA) for a systemic real-time monitoring of lower ionosphere. JASA has been developed in 2012 and improved as a real-time lightning location network since 2018. We analyze numerous thunderstorm-day data and the preliminary results show that the lower ionosphere virtual height descends linearly at a rate of 5.9 km/h during sunrise, whereas rises linearly at a rate of 8.6 km/h during sunset. Moreover, the lower ionosphere virtual height short-time fluctuation is significantly modulated by the solar radiations’ flux density recorded by GOES satellite and the lower ionosphere diurnal variation pattern exhibiting a significant asymmetry, indicating that electron production in the lower ionosphere is dominated by the effect of solar radiation accelerating the neutral atmospheric molecules

Light absorption in the photosynthetically active (400 – 700 nm) spectral region is necessary for plant CO2 fixation via photosynthesis. Light absorption in excess of that which can be used for photosynthesis may result in photoinhibition and/or other processes detrimental to normal plant function. Plants have evolved several photoprotective mechanisms to reduce light absorption under stressful conditions. For example, leaf-level reflectance and transmittance increased as a result of chloroplast movement within leaf cells in response to water stress in greenhouse-grown maize and soybean. This has implications for detecting (as a signal and noise) diurnal and stress-related changes in canopy reflectance in field-grown crops. These changes were recently investigated in the field using newly developed instrumentation systems and software. Two hyperspectral spectrometers, an Ocean Optics QE Pro (0.3 nm resolution in the 650 - 813 nm range) and a Flame (2.0 nm resolution in the 340 - 1028 nm range) are coupled through optical shutters to a downward looking fiber (25° field of view) and an upward looking fiber with cosine corrector. The spectrometers can be configured to see sky or surface targets concurrently or separately. This new configuration offers concurrent measures of derived solar induced fluorescence (SIF), and visible and near infrared reflectance on a mobile platform, acquiring spatially averaged responses. Our goal is to use SIF as an indicator of the level of photosynthetic activity in comparison to reflectance-derived indication of photoprotective response. In conducting data acquisition, several technical issues arose. Different spectrometer integration times, due to differing radiometric sensitivities and changing sky conditions, causes differences in measured reflectance between the two spectrometers. Also the approach highlighted the difficulty of obtaining reliable system calibration under varying sky conditions when using near-Lambertian reference panels. While results are promising in detecting SIF along with more conventional remote sensing spectral resolution, further research is needed to refine data acquisition to ensure quality reflectance measurements. We report on technical issues and on our success in tying photoprotection to changes in photosythentic activity.

Environmental decision- and policy-making must contend with uncertainty about the future that can hinder proactive environmental decisions, forcing environmental managers into reactive postures. To help prevent this, a variety of methods exist for exploring potential environmental futures and associated uncertainties. Producing environmental futures benefit those involved by supporting a systems-level understanding and expanding thinking beyond “business as usual”. We review environmental and non-environmental programs that use indicators to inform environmental futures for decision- and policy-making. Review objectives are to: 1) identify and discuss key environmental futures program attributes, and 2) propose program attributes that support their successful uptake in decision processes. Attributes discussed include purpose and audience, methods, addressing uncertainty and assumptions, relationship to indicator programs, how program values and biases are addressed, the role of goals, and how success is measured and defined. We conclude with recommendations for environmental futures programs that can be successfully integrated into environmental decisions. These include: combining multiple environmental futures methods to provide complementary insights or highlight inconsistencies in assumptions, including a schematic of assumptions and drivers, and defining success criteria, whenever possible. These can help increase the acceptance of environmental futures products in decision-making and increase their short-term and long-term contributions.

Thermophilic composting within ecological-based sanitation systems (EcoSan) facilitates a biogeochemical transformation of pathogenic solid materials into a sanitary organic soil amendment. Recent work suggests that, in addition to recycling nutrients and eliminating pathogens, thermophilic composting during EcoSan can lower greenhouse gas emission compared to other waste treatment practices, however empirical observations of gas fluxes are few. Data are particularly lacking from urban areas in the global south where innovation in sanitary infrastructure is a sustainable development priority. We quantified greenhouse gas emissions with intensive chamber-based flux sampling over three cycles of thermophilic composting at an established EcoSan operation serving an urban community in northern Haiti. We asked: (1) How do dynamics of greenhouse gases vary throughout the lifetime of the compost pile and the different operational stages? (2) What fraction of initial carbon and nitrogen content is lost via gas fluxes and how does this compare to internationally defined emissions factors? (3) How can different pile management options further mitigate emissions? We found methane emissions were highest in the thermophilic stage, ranging from 5-20 µmol m-2 s-1, and dominated the global warming potential of the entire operation. Approximately 0.1-0.5% of initial pile carbon was emitted as methane while only 0.05-0.3% of initial pile nitrogen was emitted as nitrous oxide, both at the low end of IPCC emissions factor ranges for manure composting. In paired-pile experiments, we found that improved pile drainage could further mitigate methane emissions, as could use of a thinner layer of cover material. This study provides some of the first detailed observations of greenhouse gas dynamics during the thermophilic composting of human waste and our results suggest that climate mitigation potential associated with composting-based EcoSan is greater than previously thought.

In this study, we have developed a hyper-resolution land-surface forcing dataset (temperature, pressure, humidity, wind speed, incident longwave and shortwave radiation) from coarse resolution products using a physically-based downscaling approach. These downscaling techniques rely on correlations with landscape variables, such as topography, temperature lapse rate corrections, surface roughness and land cover. A proof-of-concept has been implemented over the Oklahoma domain, where high-resolution observations are available for validation purposes. The hourly NLDAS (North America Land Data Assimilation System) forcing data at 0.125° have been downscaled to 500m resolution over the study area during 2015. Results show that correlation coefficients between the downscaled forcing dataset and ground observations are consistently higher and biases are lower than the ones between the NLDAS forcing dataset at their native resolution and ground observations. Results are therefore encouraging as they demonstrate that the 500m forcing dataset has a good agreement with the ground information and can be adopted to force the land surface model for land state estimation. The Noah-MP land surface model is then forced with both the native resolution NLDAS dataset and the downscaled one to simulate surface and root zone soil moisture. Model outputs are compared with in situ soil moisture observations and SMAP (Soil Moisture Active Passive Mission) products at different spatial resolutions. This work will result in a radical improvement over the current state-of-the-art forcing data and will move into the era of hyper-resolution land modeling.

Sea ice plays a crucial role on the ocean and is one of the most sensible indicators of climate change (IPCC 2013). The changing sea ice can be characterized by 4 Essential Climate Variables (ECVs) identified by the World Meteorological Global Organization Climate Observing System implementation plan (WMO Pub No.GCOS-200) : 1) sea ice extent, 2) sea ice concentration, 3) sea ice drift and 4) sea ice thickness. Since the 70ies, these 3 first variables are fairly well observed from space. However, before 2010 and the launch of CryoSat-2, sea ice thickness observations remain sparse and un- homogeneously distributed over time and space. In the Arctic ocean, we will show in this presentation that sea ice thickness time series can be extended to at least 16 years (2002-2017) using Envisat, CryoSat-2 and Sentinel-3 satellites with inter-missions biases calibrated and corrected. Among all potential inter-mission biases, the most impacting is certainly the transition from Low Resolution Mode (LRM) to Synthetic Aperture Radar (SAR) altimetry. This transition is particularly important over sea ice considering that the strong roughness heterogeneity, at basin scale and within the radar footprint, has different signatures in LRM and SAR modes. Here, we will focus on the transition between Envisat and CryoSat-2 common flight period (20010-2012). Results are validated against in situ observations (mooring, airborne, buoys and laser altimetry). This same methodology is applied to produce equivalent long term time series over Antarctica (2002-2017). In the southern ocean, the main difficulties rely on the severe lack of in-situ observations and on the ability to retrieve the snow depth. First results based on the Saral and Cryosat Ka-Ku frequency radar differences will be shown. Finally, we explain how this new global sea ice volume changes will provide new insights on the response to climate change. In particular, the final objective is to revisit the ocean freshwater budget and to provide a new constraint on the land ice melt contribution to sea level rise that is independent from the NASA Gravity Recovery and Climate Experiment measurements.

Demand-side management strategies based on customized feedback have proved their worth in supporting water conservation efforts and behavior change programs. Several studies in both the water and energy sectors report of observed short-term savings deriving from feedback-based programs and awareness campaigns, often based on smart metered data and high levels of customization in presenting information on resource usage to users in the form of past consumption, real-time information, peer comparison, analogies, and resource saving tips. Yet, feedback-based programs are often run as part of experimental trials with a limited duration, and their effectiveness is therefore only evaluated for a short time span, potentially overlooking rebound effects. Assessing the long-term effect of feedback information on behavior change is still an open research question. In this work, we analyze the long-term impacts of a smart-meter fed gamified ICT platform providing customized feedback to water users, which was deployed starting in 2014 in a long experiment trial with over 200 users of the Global Omnium utility in Valencia (Spain). The platform core is a data-driven demand management pipeline that enables water utilities to foster consumer engagement and promote water conservation via customized feedbacks. It includes customized water saving tips, peer-comparison of water usage, and a reward program based on gamification tools and mechanisms. After three years of development and testing from 2014 to 2017, the platform has proven to be very effective in the short-term, when a user is engaged. A 5.7% volumetric water use reduction among Global Omnium users was achieved after the first year of full implementation, along with a 20% approximate water consumption difference with respect to non-platform users. Here, we analyze the smart meter data of the platform users, respectively after one and two years from the end of the funded platform trial period, to assess long-term behavior changes and rebound effects on different groups of platform adopters.

The Southern Great Plains (SGP) experiences weather that is dramatic and consequential, from hurricanes and floods to heat waves and drought. A changing climate exacerbates these extremes, further stressing infrastructure and seriously impacting the socioeconomic systems of its rapidly growing and diverse 34-million population, as well as the natural environment (e.g., ecology, coastal systems). This poster will outline some of the key climate-related stressors for the SGP, and discusses the process of developing the SGP chapter and its key messages/focus areas, for the U. S. Global Change Research Program’s (GCRP) Fourth National Climate Assessment (NCA4). NCA4 fulfills a congressional mandate to provide comprehensive information on climate change impacts, adaptation, and resiliency, and is the preeminent source for climate change information within the United States. The SCP chapter is new for NCA4, providing more regional context and detail relevant to the region’s public and decision-makers than NCA3 (2014), the former of which amalgamated climate projections and impacts for the northern and southern Great Plains. Furthermore, the chapter incorporates some new ways of evaluating risk, such as risk-based framing, or in providing some more relevant context, by including potential economic impacts, and also in considering case studies of successful adaptations to current climate-related stressors. A team of regional experts consisting of climatologists, researchers, and federal scientists, spanning multiple sectors (agriculture, economy, climate science, tribal professional, infrastructure, health and water resources among others) were selected to develop this chapter. The team solicited expert input from regional stakeholders, and the final chapter underwent multiple rounds of public and governmental review. Each stage of the process and some key outcomes will be described.

MHD wave phenomena have been readily observed in recent years in various magnetic elements found within the solar atmosphere. They are often touted as a possible mechanism in channeling energy to the outer layers of the solar atmosphere. Recent advances in both observational techniques and instrumentation has gradually bridged the gap between observations and theory of these phenomena, as various wave modes have been identified and their properties studied across a wide range of structures. For example, numerous contemporary studies have identified and studied the properties associated with compressible sausage modes in different bandpasses, often employing magnetic pores as a test bed. However, the spatial structuring of the mode within the flux tube, that is, the surface and body characteristics, has thus far been ignored in observational studies. We employed high spatial and temporal resolution observations from a combination of both ground- (ROSA) and space-based (SDO) instrumentation to study several pore datasets, which were observed to support sausage modes. Using a range of techniques, we observed and were able to classify, for the first time, the surface and body characteristics for the wave modes observed within the pores. The most frequently occurring oscillation period in our observations was found to be ~300s, which is consistent with the p-mode spectrum. We find surface modes more frequently in the data. We find frequencies in the range of ~2–12 mHz, with body modes as high as 11 mHz, but we do not find surface modes above 10 mHz. Estimates made for the energetics of these wave modes will also be discussed within the context of our results.

A variety of measurements of methane in the Martian atmosphere have been made over the past 15 years, showing wildly varying indications of methane abundance, location and lifetime in the Martian atmosphere. Attempts have been made to use numerical tools such as general circulation models (GCMs) to identify source locations and timing of methane releases, but these remain inconclusive under the current approach of forward-trajectory plume modeling. Here we present results using a novel, complementary method of localizing methane surface sources by modeling passive tracer trajectories backwards in time from the locations where observations of atmospheric methane have been made. Such back-trajectory modeling employs both GCM modeled winds and a Lagrangian particle dispersion model to isolate potential upwind sources of the observed signals. This approach avoids many of the pitfalls inherent in forward-trajectory modeling approaches such as numerical diffusion and subgrid-scale motion which cannot be captured in the Eulerian framework of a GCM. We have chosen to focus on localization of the detection of methane by the Planetary Fourier Spectrometer near Gale crater around Ls=336° in MY 31. This observation is consistent with a near-coincident enhanced methane ‘spike’ observed by the Mars Science Laboratory TLS instrument. We have chosen to use the Stochastic Time-Inverted Lagrangian Transport (STILT) particle dispersion model in conjunction with the Mars Weather Research and Forecasting (MarsWRF) GCM for our back-trajectory modeling. To date, we have combined MarsWRF output with a more basic trajectory model, which advects particles based on bulk winds, and have found areas of enhanced tracer density to the north of Gale crater at prior times. Incorporation of turbulent processes in the planetary boundary layer will subject these preliminary results into test. And geological context will also be used to constrain the likelihood of these methane source locations.

The American Association for the Advancement of Science’s Leshner Leadership Institute for Public Engagement with Science, founded in 2015, empowers scientists and engineers to develop and implement public engagement activities, mentor other scientists in their communities and promote public engagement within their institutions. Each year the AAAS Leshner Leadership Institute brings together 15 mid-career researchers working on a topic at the nexus of science and society for a week of intensive training, public engagement practice, and planning. During the following year at their home institutions, AAAS Leshner Fellows implement their plans, interact via regular virtual meetings and receive additional support from staff and experts in the field of public engagement. One of the goals of the AAAS Leshner Leadership Institute is to catalyze institutional change: building understanding about, capacity for and support of public engagement within the various institutions with which researchers are affiliated. AAAS Leshner Fellows have sought to identify opportunities for institutional change within a variety of settings, including universities, government agencies and professional societies. This presentation will provide examples of institutional change from the first three cohorts of AAAS Leshner Fellows (2016-17, climate change; 2017-18, infectious disease; 2018-19, food and water security), including the ways in which they have worked to integrate public engagement into the purpose of the institutions, build processes to support public engagement, and empower people within the institutions to participate in public engagement. It will also discuss the opportunities and challenges for encouraging institutional change via a distributed network of individuals who are linked by discipline but not (necessarily) by institution.

The Sun’s chromosphere is a highly dynamic, partially ionized region where spicules (hot jets of plasma) form. Here we present a two-fluid MHD model to study the chromosphere, which includes ion–neutral interaction and frictional heating. Our simulation recovers a magnetic-canopy shape that forms quickly, but it is also quickly disrupted by the formation of a jet. Our simulation produces a shock self-consistently, where the jet is driven by the frictional heating, which is much greater than the ohmic heating. Thus, our simulation demonstrates that the jet could be driven purely by thermal effects due to ion–neutral collisions and not by magnetic reconnection. We plan to improve the model to include photo-chemical effects and radiation.

Okmok volcano on Umnak Island, Alaska is one of the most hazardous, explosive volcanoes in the Aleutians. Most recently, it erupted in 2008. Previous seismic imaging of Okmok’s large caldera system revealed complex magmatic structures in the upper 5 km beneath the caldera but magma transport at larger depths remains poorly constrained due to reduced imaging resolution. Using receiver function analysis of waveforms, we aim to chart sharp boundaries in the crust beneath Okmok and the surrounding region in order to understand its deeper crustal magmatic system. We have calculated receiver functions for M6 and larger teleseismic earthquakes between 2008 and 2021 recorded by permanent networks AV and AK, and between 2015-2016 at temporary network 5F. We observe Ps arrivals that are consistent with a Moho depth of ~40km, particularly at stations outside the caldera. At some stations, we observe that receiver functions calculated for incoming rays pointing towards the volcano are different from those pointing away from the volcano. However, there is significant variability in the receiver functions, even for overlapping ray paths in the mid-to-deep crust (> 10 km). This suggests complex crustal structure with heterogeneity that may be spatially localized beneath individual stations. Furthermore, receiver functions for stations inside Okmok caldera are more reverberatory than those outside the caldera, indicating that the structure, likely predominantly in the upper crust, beneath these two regions is different.

The Cabled Observatory Vent Imaging Sonar, otherwise known as COVIS, has acquired several months of plume centerlines and strengths for several vents in the ASHES vent field of Axial Seamount. COVIS was initially installed at ASHES vent field in July 2018 and acquired imaging data throughout July-September 2018 and since July 2019. COVIS uses acoustic imaging to monitor the strength and behavior of the plumes formed above black smokers and diffuse discharge sites in an approximately 40 m by 40 m region which includes Inferno and Mushroom vents. Preliminary observations suggest that the plumes above Inferno are highly variable; sometimes a distinct rising column is seen to expand with height while other times there is little acoustic evidence for a plume at all. Potential explanations range from variable discharge rates to variable discharge salinity driving collapsing plumes to extremes in bottom currents. The obvious simple explanation of bent plumes produced by extreme bottom currents is unsatisfactory as such bent (even horizontal) plumes should be visible in the acoustic imaging data. Initial explorations of the impact of near seawater salinity variations suggest this is a plausible explanation for variations in plume maximum height independent of heat content. However, the paucity of recent or continuous salinity and temperature sampling on Inferno limits the certainty of interpretations suggesting variations in venting. In contrast to the variable plumes, the sulfide mounds of the region (Inferno, Mushroom, Hell and Phoenix) appear as consistent (stable) silhouettes in the acoustic images. On Inferno, we can even see indications of the thin chimneys on top of the mound from which primary venting occurs. Preliminary work is focused on refining the classification of acoustic returns between rock, sulfide, and water to see if we can track the growth (and collapse) of the actively venting chimneys.

In November 2017, the High Resolution Ensemble Forecast version 2 (HREFv2) system was implemented by the U.S. National Oceanic and Atmospheric Administration (NOAA). The HREFv2 is NCEP’s first operational convection-allowing model (CAM) ensemble and runs twice daily at ~3-km horizontal grid spacing. Coinciding with the operationalization of the HREFv2, the NOAA National Weather Service’s Storm Prediction Center (SPC) launched its HREF Ensemble Viewer (https://www.spc.noaa.gov/exper/href), a public web display for real-time HREF data. In addition to products traditionally used in operational forecasting, the HREF Ensemble Viewer also employs post-processing and visualization techniques which leverage the convective structures explicitly modeled in CAM ensembles. This presentation describes and illustrates products from the SPC viewer unique to CAM ensembles which are targeted at forecasting convective storm coverage, intensity, and evolution. A key aspect of HREF’s ensemble design is membership diversity with respect to model cores and parameterization schemes, in conjunction with a time-lagging approach. Verification is performed on ensemble fields related to explicitly modeled convection for various modified configurations of the HREF membership, illustrating how each dimension of membership diversity contributes to the system’s skill in forecasting convective evolution. These results help to illuminate potential tradeoffs entailed in configuring future HREF iterations beyond version 2 as CAMs using new dynamical cores and parameterization schemes become available.

In almost Japanese megacities, various CO2 and CH4 emission source like industrial activity (power plant, landfills, gas factory, water processing plants), and agricultural activity (rice cultivation, pig farm) are concentrated within a few tens kilometers region. In order to estimate CO2 and CH4 emission rate for above various different sources, we newly developed airborne Imaging-spectrometer suites which consist of NIR spectrometer for O2-A band measurement and SWIR spectrometer for CO2/CH4 measurement. We also developed quick algorithm based on nonlinear fitting of synthetic spectrum to observation spectrum by optimization of column density of CO2 / CH4 and instrumental characteristic parameter simultaneously. The algorithm takes less than 20 second per 1 retrieval by using laptop computer, and we will challenge further acceleration by more than tens of times in order to realize real-time observation. For the first flight, we selected the eastern part of the Nagoya urban area, in which there are large CO2 emission sources, including a coal power plant and the transportation sector, and possible CH4 sources from agriculture, energy manufacturing, and waste that are geographically mixed. The results of observing the Hekinan power plant (coal-fired power generation) over Aichi Prefecture on Feb. 16, 2018 are shown in Figure 1. At the Hekinan Power Station, enhancement of CO2 column-averaged mole fractions are observed, and it can be seen that the high concentration area extends toward the downwind side. The accuracy of column density calculated by the quick algorithm will be validated with ground observation data. We estimated emission rate of CO2 of Hekinan Power plant.

The rhizosphere is a complex system in which many diverse and heterogeneous small-scale components (e.g, plant roots, fluids, microbes, and mineral surfaces) interact with one another, often in nonlinear ways, giving rise to emergent system behaviors. Ecosystem-scale perturbations, such as nitrogen limitation or drought, drive changes in micro-environments through a cascade of complex interacting processes, leading to a bidirectional feedback across scales between microbial and plant habitats at the microscale and ecosystem function at the macroscale. We are developing a conceptual and numerical framework for multiscale simulation of organic carbon transport, transformation, and disposition in the soil-microbe-plant continuum. The conceptual model comprises a set of directed graphs, with nodes representing system processes and states and edges representing process-state relationships. The graphs are coded in the graphviz syntax enabling dynamic web visualization. Graph nodes are hyperlinked to metadata pages summarizing current understanding of each process or state and its representation in current numerical codes. This conceptual model is available via a git repository and can guide identification of opportunities for coupling (data exchange) between codes operating at different length scales. The numerical implementation of the conceptual model is based on execution of integrated data processing and multiscale modeling scientific workflows. The numerical framework is enabled by a recent development in information technology known as orchestration, a class of solutions to problems of deployment and execution of cloud-oriented software. Orchestration technology is well-suited to automating complex scientific workflows, both in model-coupling efforts and experimental analysis pipelines. Here it is used to flexibly define workflow steps based on precedent events (such as arrival of a new model output in the data repository). It is being applied to integrate several community software packages spanning scales from molecules to ecosystems, linked to experimental data from the Environmental Molecular Sciences Laboratory (a national scientific user facility), to address critical scientific questions related to soil nutrient cycling.

In upland soils in humid climates, mineral stabilization of organic matter (OM) on millennial scales is often driven by the abundance of poorly crystalline, metastable chemical weathering products. Studies of volcanic ash soils have demonstrated that these metastable materials transform into increasingly crystalline minerals at advanced stages of weathering, so that the overall affinity of mineral surfaces for OM declines with time. However, the abundance of clay-sized (<2 𝜇m diameter) particles tends to increase with weathering, enhancing soil specific surface area (SSA) and potentially compensating for the loss of mineral affinity for OM. As a first step towards understanding the net effects of these simultaneous transformations on OM stabilization, we compared the coverage of SSA by OM in A and B horizons of ash-derived soils sampled along an elevation gradient in Veracruz, Mexico. N2 adsorption isotherms and Brunauer–Emmett–Teller (BET) theory were used to estimate SSA of bulk soil versus samples from which OM had been removed via combustion (muffling) and chemical oxidation (bleaching). In addition to comparing the effectiveness of the OM removal treatments, we characterized the extent to which the treatments altered the mineral matrix and introduced errors into the estimates of mineral SSA. Pore size distribution was estimated via density functional theory as a complement to the BET analysis. N2-accessible SSA ranged from 9 to 105 m2 g-1 after removal of OM, with muffling yielding higher values than bleaching for most samples. The probable loss of SSA associated with mineral transformations (e.g., of Fe oxides) at high temperatures during muffling was evidently offset by the more thorough removal of OM by that treatment. Although SSA tended to increase with weathering status, relative coverage of SSA by OM was relatively consistent across profiles and tended to be greater on average in A horizons (bleaching: 45% SSA covered, muffling: 51%) than in B horizons (bleaching: 28%, muffling: 34%). The apparent lack of OM coverage of SSA in the B horizon of the most weathered soil (0% of 60 m2 g-1 covered) underscores the overall importance of mineral reactivity in determining OM stabilization. Future work will extend these analyses to examine land-use effects on SSA coverage by OM.